72 lines
2.0 KiB
Python
72 lines
2.0 KiB
Python
from typing import TYPE_CHECKING
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from ...utils import (
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DIFFUSERS_SLOW_IMPORT,
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OptionalDependencyNotAvailable,
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_LazyModule,
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get_objects_from_module,
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is_torch_available,
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is_transformers_available,
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)
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_dummy_objects = {}
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_import_structure = {}
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try:
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if not (is_transformers_available() and is_torch_available()):
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raise OptionalDependencyNotAvailable()
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except OptionalDependencyNotAvailable:
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from ...utils import dummy_torch_and_transformers_objects # noqa F403
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_dummy_objects.update(get_objects_from_module(dummy_torch_and_transformers_objects))
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else:
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_import_structure["camera"] = ["create_pan_cameras"]
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_import_structure["pipeline_shap_e"] = ["ShapEPipeline"]
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_import_structure["pipeline_shap_e_img2img"] = ["ShapEImg2ImgPipeline"]
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_import_structure["renderer"] = [
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"BoundingBoxVolume",
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"ImportanceRaySampler",
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"MLPNeRFModelOutput",
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"MLPNeRSTFModel",
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"ShapEParamsProjModel",
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"ShapERenderer",
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"StratifiedRaySampler",
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"VoidNeRFModel",
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]
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if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
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try:
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if not (is_transformers_available() and is_torch_available()):
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raise OptionalDependencyNotAvailable()
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except OptionalDependencyNotAvailable:
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from ...utils.dummy_torch_and_transformers_objects import *
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else:
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from .camera import create_pan_cameras
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from .pipeline_shap_e import ShapEPipeline
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from .pipeline_shap_e_img2img import ShapEImg2ImgPipeline
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from .renderer import (
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BoundingBoxVolume,
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ImportanceRaySampler,
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MLPNeRFModelOutput,
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MLPNeRSTFModel,
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ShapEParamsProjModel,
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ShapERenderer,
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StratifiedRaySampler,
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VoidNeRFModel,
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)
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else:
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import sys
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sys.modules[__name__] = _LazyModule(
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__name__,
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globals()["__file__"],
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_import_structure,
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module_spec=__spec__,
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)
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for name, value in _dummy_objects.items():
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setattr(sys.modules[__name__], name, value)
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